Master of Science in Data Science

USF's one-year Master of Science in Data Science (MSDS) program delivers a rigorous curriculum focused on mathematical and computational techniques in the field of data science. The curriculum emphasizes the careful formulation of business problems, selecting effective analytical techniques to address those problems, and communicating solutions in a clear and creative fashion. All students gain real world experience for nine months out of the twelve month program (15 hours/week) tackling data science and analytics problems at companies around the San Francisco Bay Area and beyond.

Students will- Possess a theoretical understanding of classical statistical models (e.g., generalized linear models, linear time series models, etc.), as well as the ability to apply those models effectively. Possess a theoretical understanding of machine learning techniques (e.g., random forests, neutral networks, naive Bayes, k-means, etc.), as well as the ability to apply those techniques effectively. Effectively use modern programming languages (e.g., R, Python, SQL, etc.) and technologies (AWS, Hive, Spark, Hadoop, etc.) to scrape, clean, organize, query, summarize, visualize, and model large volumes and varieties of data. Prepare for careers as data scientists by solving real-world, data-driven, business problems with other data scientists, and understand the social, ethical, legal, and policy issues that increasingly challenge and confront data scientists.

Applicants who hold a bachelor's degree in any field and have fulfilled the MS in Data Science prerequisites are considered for admission. Applicants with academic or professional backgrounds in math, computer science, engineering, finance, economics or equivalent skills are encouraged to apply
Transcript (Academic Record)
Statement of Purpose
Resume or CV
Letters of Recommendation

IELTS- 6.5
TOEFL- 90, Minimum iBT subscore- 17